Abstracts of Summer Research Projects:

The Interaction of Chemotherapy with Cancer and Normal Cells: A Quantitative Study

Marissa Stewart | Department of Mathematics

Advisor: Dr. Sanjukta Hota, Department of Mathematics

Abstract:

Cancer occurs when certain cells in the body keep dividing and form more cells without the ability to stop the process. There are many treatment types for cancer that come with different results. The most common treatment used by oncologists is chemotherapy which refers to drugs used for treating cancer. These drugs, after being administered into the body, interacts with both normal and cancer cells. As a result the normal cells are damaged along with cancer cells and this causes many side effects. The main objective of this project was to perform a quantitative analysis of the interaction effect of chemotherapy drugs with cancer and normal cells. A logistic mathematical model was developed using a system of ordinary differential equations (ODE) involving cancer cells, normal cells, and chemotherapy drugs. The effects of the drugs on the cells were investigated by performing the stability analysis of the ODE system at equilibria with and without chemotherapy. Numerical simulations were carried out using Mathematica to explore various cases during chemotherapy treatment. The parameter values used in the model were obtained either from references in the literature or from previous studies on this topic published in the journals. The results showed that both normal and cancer cells were affected by the drug at different intensities and the interaction varies with the environment and the aggression of the cells. Conditions for cancer-free state and intermediate state in terms of relevant model parameters were derived and numerical results were illustrated.

Computational Approaches for Understanding RAGE Activation

Isis Christopher | Department of Chemistry

Advisor: Darlean Martin and Dr. Steven Damo, Department of Chemistry

Abstract:

The receptor for advanced glycation end products (RAGE) is a critical cell surface pattern recognition receptor that is in involved in the inflammatory processes of the human body. Misregulation of RAGE expression is connected to tumor outgrowths, diabetic complications, and neurodegenerative disorders, which are increasing worldwide concerns. Hence, RAGE is a potential target for therapeutic intervention. RAGE is able to bind to a variety of ligands, such as the superfamily of S100 proteins. Ligands S100A12 and S100P possess very similar structures, but each exhibit distinguishable functions. The binding of the RAGE protein with such ligands at the RAGE extracellular VC1 domain induces a cascade of cellular signaling events, which implements the expression of proinflammatory molecules along with new RAGE molecules. Understanding the molecular mechanisms and interactions that induce the activation of RAGE will allow for the rational design of small molecule inhibitors with the potential to help treat and prevent such inflammatory disease. This project focuses on predicting the structure of the receptor-ligand complex of RAGE and S100A12, and validating these predictions with experimental approaches as well as comparisons to previously determined experimental structures of homologous proteins. Protein-protein docking was performed using ZDOCK (http://zdock.umassmed.edu/), a web based interface used as a tool to create computational predictions of the structure of protein-protein complexes. The ten models with the lowest energy were analyzed using Chimera (UCSF Chimera--a visualization system for exploratory research and analysis. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. J Comput Chem. 2004 Oct;25(13):1605-12.) and PDBePISA (http://www.ebi.ac.uk/pdbe/pisa/). Although S100A12 and S100P have similar structures, the binding surfaces of these ligands with RAGE were found to be located on opposing faces of the RAGE molecule. However, in both structures, Arginine 104 is a critical interfacing residue of the RAGE molecule. Computational evidence also suggests that RAGE residues Glutamine (47, 67) Proline (46, 66, 71), and Glycine (69, 70) also play an important role in the receptor-ligand binding complex of RAGE. Validation of these results may be tested by performing experimental techniques in order to compare the binding affinities of wild type RAGE with that of mutated RAGE.

Caenorhabditis elegans, also known as C. elegans, is said to be the model worm for scientific studies and inquiry. Though this system is relatively simple (with only around 1000 somatic cells in the hermaphrodite form), much of their molecular and cellular function is homologous to that of Homo sapiens. Using a compiled list of over 1200 C. elegans genes expressed in dopamine (DA) neurons, I set out to find the human homologs. Along with the list of C. elegans DA genes, information from both the WormBase site and Online Mendelian Inheritance in Man (OMIM) site were also used. This process, however, takes a lot of time to manually navigate and to decipher all of the information. With the use of computer programming, we simplified the process by establishing a program to annotate a list of genes.

In my second project, I analyzed the dopamine neuron degeneration in C. elegans that have been exposed to copper. Patients with Parkinson’s disease (PD) not only have dopaminergic neurodegeneration, but also tend to have higher levels of metals (such as iron, copper, and manganese) in their systems. With the hypothesis that exposure to metal can lead to neurodegeneration associated with early onset of PD, I analyzed the effect that copper has on dopamine degeneration in the C. elegans species, and what genes were involved. My experiment exhibited some dopamine degeneration. This finding may correlate with the hypothesis and provide insight into Parkinson’s disease and other diseases that involve dopaminergic neurodegeneration. But I completed only one trial. So my next step goal is to complete more trials to provide more conclusive result.

Human Immune Deficiency (HIV) virus infects CD4 Cells (T-cells) whose function is to protect the human body from infections and diseases. A healthy, uninfected person has between 800 to 1200 CD4 cells per cubic millimeter of blood. Once the CD4 cells count decreases to 200 cells per cubic millimeter, the immunity is damaged and vulnerable to infections and diseases.

My goal of the project is to study mathematically how the HIV virus weakens the immune system. A basic differential equation model is developed to describe the interaction of immune system of the body with HIV virus. The equilibrium points, both Disease Free and Endemic, are determined and the basic reproductive ratio is found. Finally I show how the model can be used to demonstrate the effect of antiviral therapy on reducing the infection rate due to the free virus. Computational software Mathematica is used for all simulations and graphs included in the project.

Investigating New Dopaminergic Neuron Genes

Zaria Maynard | Department of Biology, Alabama State University

Advisor: Dr. Brian Nelms,Department of Biology

Abstract:

My research work consists of two individual projects. The first project is a group project with Sharee and Cassie . We have a dataset (from another lab) of genes that are expressed in dopaminergic neurons in C. elegans, a small worm we are using as a model. We have created a computer program that extracts the gene identification from an Excel file and link it to information to the website WormBase for the homology with human genes and related diseases. This project helps to automate the process of comparing different genes that is expected to be involved in dopaminergic functions in C. elegans and humans, making comparisons much easier and less time consuming.

The second project deals with genes related to Parkinson's diseases and memory loss. When there is an abnormal level of dopamine in the prefrontal cortex of humans, it can lead to memory loss. In this experiment I determine what amount of dopamine causes memory loss, for example high levels or low levels. In Parkinson's disease, patients have a very low level of dopamine in their brain, and the doctors prescribe the drug LDOPA to help produce more dopamine. When this drug is not capable of producing a sustainable amount of dopamine, doctors have learned to use a COMT inhibitor to help LDOPA continuously provide dopamine in the individual.

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